A Particle Swarm Optimisation-trained Feedforward Neural Network for Predicting the Maximum Power Point of a Photovoltaic Array

Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/20776

Full metadata record

DC Field	Value	Language
dc.contributor.author	Almajidi, S	-
dc.contributor.author	Abbod, M	-
dc.contributor.author	Al-Raweshidy, H	-
dc.date.accessioned	2020-05-05T20:02:06Z	-
dc.date.available	2020-05-05T20:02:06Z	-
dc.date.issued	2020	-
dc.identifier.issn	0952-1976	-
dc.identifier.uri	http://bura.brunel.ac.uk/handle/2438/20776	-
dc.description.sponsorship	Iraqi Ministry of Higher Education and Scientific Research	en_US
dc.language	English	-
dc.language.iso	en	en_US
dc.publisher	Elsevier	en_US
dc.subject	Artificial neural network (ANN)	en_US
dc.subject	Fuzzy Logic Control (FLC)	en_US
dc.subject	Maximum Power Point tracking (MPPT)	en_US
dc.subject	Photovoltaic (PV)	en_US
dc.subject	Perturb and Observe (P&O)	en_US
dc.subject	Efficiency of MPPT (η MPPT)	en_US
dc.title	A Particle Swarm Optimisation-trained Feedforward Neural Network for Predicting the Maximum Power Point of a Photovoltaic Array	en_US
dc.type	Article	en_US
dc.relation.isPartOf	Engineering Applications of Artificial Intelligence	-
pubs.publication-status	Accepted	-
Appears in Collections:	Dept of Electronic and Electrical Engineering Embargoed Research Papers

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